CHAPTER 1: Data Collection and Presentation

Statistics is derived from the Latin word “___” meaning state

status

In plural sense, it is defined as any set of numerical data (e.g. vital statistics, monthly sales)

STATISTICS

In singular sense, it is defined as a branch of science that deals with the collection, presentation, analysis, and interpretation of data

STATISTICS

• without drawing conclusions or inferences from it

• tables, graphs, frequency, mean, etc.

Descriptive Statistics

• utilizes sampled data to make inferences about the population

• hypothesis testing, determining relationships, making predictions

Inferential Statistics

facts or figures from which conclusions may be drawn

Data

collection of facts and figures or data

Data Set

entities on which data are collected

Elements/Units

a characteristic or attribute of elements which can assume different values or labels under statistical study

Variable

set of measurements collected for a particular element

Observation

Types of Variables

• Qualitative

• Quantitative

• outcomes of the variables expressed non numerically or categorically

• example: name, gender, eye color, religion, etc.

Qualitative

• outcomes are expressed numerically that are meaningful or indicate some sort of amount

• example: age, allowance, number of students, height, etc.

Quantitative

Kinds of Quantitative Variables

• Discrete

• Continuous

• a variable which can assume finite, or at most , countably infinite number of values

• usually measured by counting

• answers the question “how many”

• example: # of students, # of children

Discrete

• a variable which can assume infinitely many values corresponding to a line interval

• gives rise to measurement

• answers the question “how much”

• example: weight, allowance, height

Continuous

Scale/Levels of Measurement of Variables

1. Nominal
2. Ordinal
3. Interval
4. Ratio

• classificatory scale

• weakest level of measurement where numbers or symbols are used simply for labeling or categorizing subjects into different groups

Nominal

• classificatory with ordering scale

• numbers assigned to categories of any variable may be ranked or ordered

Ordinal

has the properties of the nominal and ordinal levels

Interval •

• highest level of measurement

• has the properties of the nominal, ordinal, and interval levels

• anything that is countable or measurable

• has absolute zero or true zero

Ratio

Variables and Levels of Measurement

acquired directly from the original source of information

Primary Data

data taken from published or unpublished data which have been previously gathered by others

Secondary Data

means “from someone’s point of view”

Subjective Data

fact-based, measurable, countable, and observable

Objective Data

there is a person-to-person contact or exchange of information between the interviewer and interviewee

Interview

data are collected by means of written responses based on a list of questions which are relevant to the problems of the study

Questionnaire

used when the objective is to determine the cause-and-effect relationship of certain phenomena under controlled conditions

.Experimental

the researcher observes the behavior of persons and their outcomes

Observation

this method of collecting data is enforced by certain laws such as registration of births, deaths, licenses, etc.

Registration

entire group of observations or elements where inferences and conclusions are made

Population

a numerical characteristic of the population

Parameter –

subset of the entire group of observations or elements where data is collected

Sample

a numerical characteristic of the sample

Statistic

process of gathering information from every unit or all the units of the population

Census/Complete Enumeration

process of obtaining a part or subset of the population

Sampling/Survey Sampling

Types of Sampling Methods

• Probability Sampling

• Nonprobability Sampling

• have equal chances of being selected as a sample

• uses some chance mechanism

Probability Sampling

• do not have equal chances

• without regard for some chance mechanism

Nonprobability Sampling

is used because there is no objective way of assessing the reliability of inferences under non probability sampling

probability sampling

a listing of all individual units in the population, is required in the execution of probability sampling methods

The sampling frame,

2 Types of Simple Random Sampling (SRS)

1. SRS with Replacement (SRSWR)

2. SRS without Replacement (SRSWOR)

Method of selecting n units out of N units in the population where all elements in the population have an equal chance of being included in the sample

Simple Random Sampling (SRS)

a chosen element is always replaced before the next selection is made

SRS with Replacement (SRSWR)

a chosen element is not replaced before the next selection is made

SRS without Replacement (SRSWOR)

• Systematic sampling with a “random start” is a method of selecting a sample by taking every kth unit from an ordered population, where the first unit being selected at random

• __ is called the sampling interval

• Systematic Sampling

• k

It is done if the population is heterogeneous and can be subdivided into non-overlapping (𝑁1, 𝑁2,…,𝑁𝑘) called____

• Stratified Sampling

• strata.

A method of sampling where a sample of distinct groups, or clusters, of elements is randomly selected and then a census or all elements in the selected clusters is taken

Cluster Sampling

___are non-overlapping subpopulations which together comprise the entire population

Clusters

Types of Non-probability Sampling

• 1. Purposive Sampling

• 2. Convenience Sampling

• 3. Quota Sampling

• 4. Snowball Sampling